Research On Temperature Control Of The Iron Ore Metallurgical Properties Test Reduction Furnace

Over the years, the testing process of iron ore metallurgical properties relies mainly on the years experience summarized by the workers through the completed operation in the field, so lacks of theoretical and scientific property. During the test of the iron ore metallurgical performance, high-precision temperature control is an important aspect of the constraints of the experiment success, so the design of a smart, high-precision furnace temperature measurement and control system is important for the study of the accuracy of the metallurgical performance.First of all, regarding the phenomenon in the experimental field of using the conventional PID algorithm such as the large deviation, instability, associated properties of the heating element of reduction furnace which is the research object is analyzed.Since there are some uncertainties in the model parameters the fractional order PI~λD~μexpert fuzzy control algorithms is put forward through adopting the expert fuzzy control strategy combined with fractional order calculus theory to achieve the high precision control of the furnace temperature. The MATLAB software is used to simulate and analyze the effect of various parameters of fractional PI~λD~μcontroller on the system performance, then determine the fuzzy controller rule. Secondly, to achieve real-time acquisition temperature data quickly, use PCI bus technology to design hardware and software of intelligent data acquisition module. Finally, the programming environment VC++6.0 is used to design PC control interface. The control algorithm presented is used to control the experiment and is compared with conventional control algorithms tests.Experimental tests show that: The control effect of using experts fuzzy control algorithm fractional PI~λD~μ is better compared with other traditional control strategies. The dynamic performance and steady performance are improved, the overshoot is reduced,the steady-state error is reduced, and the impact of the oscillation phenomenon on system stability is overcome. It meets the control requirements of precision and achieve a reduction Furnace precision intelligent control.